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Mastering Sentiment Analysis with PySpark

Learn how to analyze sentiments efficiently using PySpark. Explore TF-IDF, N-gram, and Count Vectorizer techniques. Implement Logistic Regression for sentiment classification. Hands-on guide with training data and helpful resources.

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Mastering Sentiment Analysis with PySpark

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  1. Sentiment Analysis with PySpark Satya Katragadda March 22, 2018

  2. Goal • Perform Sentiment Analysis with spark • TF-IDF • N-gram • Count Vectorizer • Logistic Regression

  3. Import the Data

  4. Import the Data -2

  5. Training and Testing Sets

  6. Hashing TF and IDF

  7. Sentiment Analysis

  8. Another way to compute TF

  9. N-Gram Implementation

  10. N-Gram Implementation

  11. Questions: satya@Louisiana.edu Acknowledgements: https://github.com/tthustla/setiment_analysis_pyspark/blob/master/Sentiment%20Analysis%20with%20PySpark.ipynb

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